code: def learn(
      epochs,
      verbose_epoch,
      X_train,
      y_train,
      test,
      learning_rate,
      weight_decay,
      batch_size,
  ):
      """Trains the model and predicts on the test data set."""
      net = get_net()
      _ = train(
          net,
          X_train,
          y_train,
          epochs,
          verbose_epoch,
          learning_rate,
          weight_decay,
          batch_size,
      )
      preds = net(X_test).asnumpy()
      test["SalePrice"] = pd.Series(preds.reshape(1, -1)[0])
      submission = pd.concat([test["Id"], test["SalePrice"]], axis=1)
      submission.to_csv("submission.csv", index=False)
  
file_path: mxnet/example/gluon/house_prices/kaggle_k_fold_cross_validation.py
imports: import numpy
  import pandas
  from mxnet import autograd
  from mxnet import gluon
  from mxnet import np
label_desc: Use image node_id 5 for calling a global function with example usage: learn(epochs, verbose_epoch, X_train, y_train, test, learning_rate, weight_decay, batch_size) without return types